BCI is an information transmission channel between a human brain and a computer or other electronic devices. This technique does not rely on the peripheral nervous system and muscles, and therefore provide a direct brain-computer communication pathway.
Currently available BCI systems can be grouped into two categories based on methods for acquisition of human brain activities: invasive methods (e.g., ECoG and sEEG) and non-invasive methods (e.g., EEG and MEG). Invasive methods can get more accurate signals, but are not proper for daily uses due to their invasive manners. Thus, studies focus on non-invasive methods. Among existing non-invasive techniques, EEG is one of the most widely used approaches because of its practicability and low cost.
Various BCI systems have been developed by different research groups. For example, Graz BCI is a cue-based system, which was developed by University of Technology Graz (Austria). The Graz BCI system uses imagery of motor action as an appropriate mental task. Several clinical applications of Graz BCI operations for hand orthosis have been reported. The Wadworth Center (US) developed a BCI system named BCI2000, which provides a flexible general-purpose platform that facilitates the evaluation, comparison, and a combination of alternative brain signals, processing methods, applications, and operating protocols.
Traditional BCI systems require multi-channel EEG facilities for measuring brain activities, which is complex and cumbersome. Furthermore, most of these systems need PCs for analysis of EEG signals. These constraints limit applications of BCI systems in a laboratory-scale.